The Latest Trends in Quantum Computing [Part 2]

On November 20, 2018, Fujitsu hosted Fujitsu Insight 2018, which took up themes such as "AI and the IoT." The second half of the seminar entitled "Looking into the New Future Opened Up by Digital Annealer—the Latest Trends and Fujitsu's Engagement in Quantum Computing—" focused mainly on the latest trends in quantum computing and Digital Annealer case studies from the automobile industry.
[Fujitsu Insight 2018 "AI and the IoT" Seminar Report]

DENSO Endeavors to Change the World with Quantum Computers

In the second half of the seminar, Masayoshi Terabe of DENSO introduced how the company is working with the latest technology, such as the IoT and quantum computers, from a manufacturing industry perspective.

"Optimization" the Issue of the Automobile Industry's Once-a-Century Reform Period

I am trying to change the world using quantum computers. Combinatorial optimization's impact can change society. For example, in a traffic jam, I believe everyone thinks they want to be first to get to their destinations. This causes everyone to look for less crowded roads once the roads they are on become crowded. This makes the less crowded roads then become crowded, so traffic jams never disappear. However, if everyone thinks we should all get to our destinations quickly, there will be no traffic jams, and everyone will be pleased. Quantum annealing can create "a new society that pleases everyone."

So, what I am doing is providing a new kind of joy through quantum annealing, which can execute superfast optimization that can change society.

The automobile industry is said to be in a once-a-century reform period. The keywords for this reform are electrification (electric vehicles), self-driving, and connected cars. You may hear these terms quite often, but what they represent is not technology but rather the market and services. If you think of large batteries running around a city, you may come up with an electric transportation service. If such batteries connect to the Internet, some of you may think about developing apps for automobiles like apps for smartphones. Previously, we conceived of the automobile business as selling items. Going forward, however, the market for automobile-enabled services will expand. This kind of market will be created by connected devices, namely IoT devices.

Optimization is the issue on the way to the connected future. The maturity of IoT product capabilities starts at monitoring in which sensors are installed in many parts. This is Step 1. The monitoring function visualizes the state of traffic jams. In Step 2, these sensors control product functions. In Step 3, more sophisticated control enables analysis of big data and optimization of product capabilities using analysis results. Lastly, in Step 4, autonomous product operation is achieved.

Optimization is the key issue for the future connected business.

In the automobile IoT field, cars already have many sensors. We are now in the stage of exploring what to do with the data. For this reason, Step 3, optimization, will begin in the automobile market.

Optimize the Moment—The DENSO Quantum Computing Team's Motto

At DENSO, we already operate based on the concept that there is a kind of value that can be generated by optimizing the moment. Under the motto of "Optimize the Moment," we have launched various projects using annealing machines.

To give a few examples, we are conducting Proof of Concept (PoC) experiments. In Thailand, we are working with Toyota Tsusho in a traffic app experiment. Another experiment is to improve our factory's productivity. In Thailand, we aim to create a new market by testing the app and addressing issues caused by traffic, such as traffic jams and delivery problems.

In a factory, there are daily changes related to workers and production statuses. Previously, it took too long to do optimization, so we had no choice but to execute it monthly. Now, we are conducting a PoC test based on the assumption that quantum computers can enable the factory to continuously evolve in real time.

One achievement is a 15% increase in the factory operating rate by optimizing automated guided vehicle (AGV) operation. In factory operation improvement, 15% is a remarkable figure. This experiment showed a large cost benefit because we could reduce the number of automated delivery robots by more than 10%.

Showing these experiments to external parties gives us a lot of feedback. Then, conversations move to discussing the feasibility of ideas, which results in more PoC experiments. Alleviation of traffic jams will improve the environment, energy, and people's health. This led us to realize that in-depth study of one issue may lead us to an application that can optimize all of society.

Where will we go next? There may be a large market. With the belief we will find great opportunities, we are making partners and working on technological improvement.

We began using Fujitsu Digital Annealer in August and tested its technical capabilities using factory AGV route optimization models. We expect this testing to have significant outcomes. I think Digital Annealer's strength is its ability to handle larger, socially meaningful problems.

DENSO and its future direction of Fujitsu Digital Annealer usage

Use of Digital Annealer Shifting from Testing to Practical Application

The final seminar speaker was Kentaro Fuji of Fujitsu Limited, who introduced the Digital Annealer service and its future development.

Digital Annealer cloud and technical services began in May. The technical service provides support for mathematization of the pre-processing required for annealing, introduction, and operation. We also plan to offer an on-premises service for installation in customers' data centers. Many customers have been using the technical service since launch.

The second generation of Digital Annealer will be released in December 2018. The second generation is 100 times faster than the first generation and can handle 8192-bit problems, which is far more than the first generation. We will also develop and equip a chip especially for Digital Annealer.

The first generation of Digital Annealer is at the stage in which customers are finishing testing and starting practical use. The second generation will be faster, reaching the 8000-bit class. We think it will be able to handle actual operation problems. In the future, we will develop a next-generation Digital Annealer that is smaller, more parallel, and handles one-million-bit-class problems.